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Assessment of total and extreme precipitation over central Asia via statistical downscaling: Added value and multi-model ensemble projection

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Advances in Climate Change Research 2023年第1期14卷 62-76页

作者： Li-Jun FAN Zhong-Wei YAN Deliang CHEN Zhen LI Key Laboratory of Regional Climate-Environment for Temperate East Asia Institute of Atmospheric PhysicsChinese Academy of ScienceBeijing 100029China College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijing 100049China Regional Climate Group Department of Earth SciencesUniversity of GothenburgGothenburg40530Sweden

Central Asia(CA)is highly sensitive and vulnerable to changes in precipitation due to global warming,so the projection of precipitation extremes is essential for local climate risk ***,global and regional climate models often fail to reproduce the observed daily precipitation distribution and hence extremes,especially in areas with complex *** this study,we proposed a statistical downscaling(SD)model based on quantile delta mapping to assess and project eight precipitation indices at 73 meteorological stations across CA driven by ERA5 reanalysis data and simulations of 10 global climate models(GCMs)for present and future(2081-2100)periods under two shared socioeconomic pathways(SSP245 and SSP585).The reanalysis data and raw GCM outputs clearly underestimate mean precipitation intensity(SDII)and maximum 1-day precipitation(RX1DAY)and overestimate the number of wet days(R1MM)and maximum consecutive wet days(CWD)at stations across ***,the SD model effectively reduces the biases and RMSEs of the modeled precipitation indices compared to the *** it effectively adjusts the distributional biases in the downscaled daily precipitation and indices at the stations across *** addition,it is skilled in capturing the spatial patterns of the observed precipitation ***,SDII and RX1DAY are improved by the SD model,especially in the southeastern mountainous *** the intermediate scenario(SSP245),our SD multi-model ensemble projections project significant and robust increases in SDII and total extreme precipitation(R95PTOT)of 0.5 mm d^(-1) and 19.7 mm,respectively,over CA at the end of the 21st century(2081-2100)compared to the present values(1995-2014).More pronounced increases in indices R95PTOT,SDII,number of very wet days(R10MM),and RX1DAY are projected under the higher emission scenario(SSP585),particularly in the mountainous southeastern *** SD model suggested that SDII and RX1DAY will likely rise more rap

关键词： local precipitation extremes Statistical downscaling Multi-model ensemble projection Robustness and uncertainty Central Asia

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